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Face tracking using optical flow development of a real-time adaboost cascade face tracker

dc.contributor.authorRanftl, Andreas
dc.contributor.authorAlonso-Fernandez, Fernando
dc.contributor.authorKarlsson, Stefan
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorRathgeb, Christian
dc.contributor.editorUhl, Andreas
dc.date.accessioned2017-06-30T08:19:16Z
dc.date.available2017-06-30T08:19:16Z
dc.date.issued2015
dc.description.abstractIn this paper a novel face tracking approach is presented where optical flow information is incorporated into the Viola-Jones face detection algorithm. In the original algorithm from Viola and Jones face detection is static as information from previous frames is not considered. In contrast to the Viola- Jones face detector and also to other known dynamic enhancements, the proposed face tracker preserves information about near-positives. The algorithm builds a likelihood map from the intermediate results of the Viola-Jones algorithm which is extrapolated using optical flow. The objects get extracted from the likelihood map using image segmentation techniques. All steps can be computed very efficiently in real-time. The tracker is verified on the Boston Head Tracking Database showing that the proposed algorithm outperforms the standard Viola-Jones face detector.en
dc.identifier.isbn978-3-88579-639-8
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2015
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-245
dc.titleFace tracking using optical flow development of a real-time adaboost cascade face trackeren
dc.typeText/Conference Paper
gi.citation.endPage48
gi.citation.publisherPlaceBonn
gi.citation.startPage39
gi.conference.date9.-11. September 2015
gi.conference.locationDarmstadt

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